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MINOR CHANGE: Refactor matrix coercion thanks to Matrix 1.5-0.
DOCUMENTATION: Remove comments from
generate_dataset().
DOCUMENTATION: Extend usage of
wrap_dataset().
DOCUMENTATION: Document outputs of combine_models()
and get_timings().
BUG FIX calculate_dimred(): Force deep copy of
matrix to avoid error message: “Error in x\(.self\)finalize() : attempt to apply
non-function”.
plot_feature_network(): Added workaround for
thomasp85/ggforce#273.BUG FIX generate_experiment(): Return timepoint
groups for experiment_synchronised().
BUG FIX unit tests: loosen generate partitions constraints.
MINOR CHANGE generate_dataset(): Fix subplot
title.
NEW FEATURE plot_summary(): Create a dedicated
function for plotting a dyngen summary.
BUG FIX generate_cells(): Fix incorrect cell count
when one of the backbone segments does not have any simulations steps
(#26).
DOCUMENTATION: Update citation to NCOMMS publication.
MINOR CHANGE .download_cacheable_file(): Check the
return value of utils::download.file(), since it is
possible that the download will fail with a non-zero status but not an R
error.
MINOR CHANGE kinetics_random_distributions(): Add
function for providing randomised distributions.
This version mostly upgrades dyngen’s ease-of-use, such as better vignettes, conversion functions for working with dyngen datasets in other packages, and more useful ways of specifying platform-specific parameters (i.e. number of cores and cache location). Perhaps more excitingly, the dyngen documentation is more readable online at https://dyngen.dynverse.org!
wrap_dataset(): Now returns a list instead of a dyno
object. Use as_dyno(model) or
wrap_dataset(model, format = "dyno") to replicate previous
behaviour.Added functions for converting the dyngen output to various data
formats: as_anndata() for anndata, as_sce()
for SingleCellExperiment, as_seurat() for Seurat,
as_dyno() for dyno, as_list() for a simple
list object.
wrap_dataset(): Added ‘format’ argument which allows
choosing the output format (#28).
The default number of cores used can be set by adding
options(Ncpus = ...) to your Rprofile.
The default cache folder for dyngen can be set by adding
options(dyngen_download_cache_dir = ...) to your
Rprofile.
Combine similar models with different outputs using the
combine_models() function.
Store the timings throughout the dyngen execution. Extract the
timings from a model using get_timings().
generate_experiment(): Map count density of reference
dataset to simulation expression before sampling molecules. Parameters
are available for toggling off or on the mapping of the reference
library size & CPM distribution.initialise_model(): Change defaults of
num_cores and download_cache_dir to
getOption("Ncpus") and
getOption("dyngen_download_cache_dir")
respectively.
generate_experiment(): Drastically speed up sampling
of molecules.
as_dyno(): Fix drop = FALSE bug when
only one cell is being sampled.
Removed names from feature ids in feature info
(unname(model$feature_info$feature_id)). Thanks @milanmlft!
Added and extended vignettes:
Created a website at https://dyngen.dynverse.org using pkgdown.
Shortened examples to reduce r cmd check time.
wrap_dataset(): Outputted $counts now
contains counts of both spliced and unspliced reads, whereas
$counts_unspliced and $counts_spliced contains
separated counts.
Added a docker container containing the necessary code to run a dyngen simulation.
Added logo to package.
Clean up internal code, mostly to satisfy R CMD check.
Added two vignettes.
Expanded the README.
Implement knockdown / knockouts / overexpression experiments.
Implement better single-cell regulatory activity by determining the effect on propensity values after knocking out a transcription factor.
Implement adding noise to the kinetic params of individual simulations.
Kinetics (transcription rate, translation rate, decay rate, …) are based on Schwannhausser et al. 2011.
Changed many parameter names to better explain its purpose.
Fix module naming of backbones derived from
backbone_branching().
Allow to plot labels in
plot_simulation_expression().
Improve backbone_disconnected() and
backbone_converging().
Rename required columns in backbone() input
data.
Use backbone_linear() to make
backbone_cyclic() randomised.
Added a decay rate for pre-mRNAs as well.
Kinetics: redefine the decay rates in terms of the half-life of these molecules.
Only compute dimred if desired.
Allow computing the propensity ratios as ground-truth for rna velocity.
Implement fix for double positives in bblego
backbones.
Fix graph plotting mixup of interaction effects (up/down).
Made a fix to the computation of
feature_info$max_protein.
MAJOR CHANGES: Custom backbones can be defined using backbone
lego pieces. See ?bblego for more information.
MAJOR CHANGES: Splicing reactions have been reworked to better reflect biology.
Complete rewrite from dyngen from the bottom up.
OPTIMISATION: All aspects of the pipeline have been optimised towards execution time and end-user usability.
OPTIMISATION: dyngen 0.2.0 uses
gillespie 0.2.0, which has also been rewritten entirely in
Rcpp, thereby improving the speed significantly.
OPTIMISATION: The transcription factor propensity functions have been refactored to make it much more computationally efficient.
OPTIMISATION: Mapping a simulation to the gold standard is more automised and less error-prone.
FEATURE: A splicing step has been added to the chain of reaction events.
INITIAL RELEASE: a package for generating synthetic single-cell data from regulatory networks. Key features are:
dyngen 0.1.0 uses gillespie 0.1.0, a clone
of GillespieSSA that is much less error-prone and more
efficient than GillespieSSA.igraph and generates simple single-cell
expression data using GillespieSSA.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.